New insight into Epstein-Barr virus infection using models of stratified epithelium.

Epstein-Barr virus (EBV) is a ubiquitous human pathogen that is transmitted in saliva. EBV transits through the oral epithelium to infect B cells, where it establishes a life-long latent infection. Reinfection of the epithelium is believed to be mediated by virus shed from B cells, but whether a latent reservoir can exist in the epithelia is unknown. We previously developed an in vitro organotypic model of stratified epithelium where EBV can readily replicate within the suprabasal layers of the epithelium following apical infection mediated by virus-producing B cells. Given that infected epithelial cells and cell-free virus are observed in saliva, we examined the ability of both of these to mediate infection in organotypic cultures. Epithelial-derived cell-free virus was able to infect organotypic cultures from the apical surface, but showed enhanced infection of B cells. Conversely, B cell-derived virus exhibited enhanced infection of epithelial cells. While EBV has been detected in basal cells in oral hairy leukoplakia, it is unknown whether EBV can be seen in undifferentiated primary keratinocytes in the basal layer. Undifferentiated epithelial cells expressed proposed EBV receptors in monolayer and were susceptible to viral binding and entry. Integrins, and occasionally ephrin A2, were expressed in the basal layer of gingiva and tonsil derived organotypic cultures, but the known B-cell receptors HLAII and CD21 were not detected. Following infection with cell-free virus or virus-producing B cells at either the apical or basolateral surface of preformed organotypic cultures, abundant infection was detected in differentiated suprabasal cells while more limited but readily detectable infection was observed in the undifferentiated basal cells. Together, our data has provided new insight into EBV infection in stratified epithelium.

The Epstein-Barr Virus Glycoprotein BDLF2 Is Essential for Efficient Viral Spread in Stratified Epithelium.

Epstein-Barr virus (EBV) is a ubiquitous human pathogen that infects the majority of the adult population regardless of socioeconomic status or geographical location. EBV primarily infects B and epithelial cells and is associated with different cancers of these cell types, such as Burkitt lymphoma and nasopharyngeal carcinoma. While the life cycle of EBV in B cells is well understood, EBV infection within epithelium is not, largely due to the inability to model productive replication in epithelium in vitro. Organotypic cultures generated from primary human keratinocytes can model many aspects of EBV infection, including productive replication in the suprabasal layers. The EBV glycoprotein BDLF2 is a positional homologue of the murine gammaherpesvirus-68 protein gp48, which plays a role in intercellular spread of viral infection, though sequence homology is limited. To determine the role that BDLF2 plays in EBV infection, we generated a recombinant EBV in which the BDLF2 gene has been replaced with a puromycin resistance gene. The ΔBDLF2 recombinant virus infected both B cell and HEK293 cell lines and was able to immortalize primary B cells. However, the loss of BDLF2 resulted in substantially fewer infected cells in organotypic cultures compared to wild-type virus. While numerous clusters of infected cells representing a focus of infection are observed in wild-type-infected organotypic cultures, the majority of cells observed in the absence of BDLF2 were isolated cells, suggesting that the EBV glycoprotein BDLF2 plays a major role in intercellular viral spread in stratified epithelium. IMPORTANCE The ubiquitous herpesvirus Epstein-Barr virus (EBV) is associated with cancers of B lymphocytes and epithelial cells and is primarily transmitted in saliva. While several models exist for analyzing the life cycle of EBV in B lymphocytes, models of EBV infection in the epithelium have more recently been established. Using an organotypic culture model of epithelium that we previously determined accurately reflects EBV infection in situ, we have ascertained that the loss of the viral envelope protein BDLF2 had little effect on the EBV life cycle in B cells but severely restricted the number of infected cells in organotypic cultures. Loss of BDLF2 has a substantial impact on the size of infected areas, suggesting that BDLF2 plays a specific role in the spread of infection in stratified epithelium.

Exposure-efficacy and exposure-safety analyses of ropeginterferon alfa-2b treatment in patients with polycythaemia vera.

AIMS: To investigate the exposure-response (E-R) relationship, including exposure-efficacy and exposure-safety, of ropeginterferon alfa-2b treatment in patients with polycythaemia vera (PV). METHODS: Based on the results of the phase II trial A20-202 regarding ropeginterferon alfa-2b in patients with PV, E-R analyses were performed to evaluate the efficacy and safety of the given dosing regimen. The E-R analyses were based on logistic and linear regression and the relationship between exposure to ropeginterferon alfa-2b and key efficacy and safety variables. The key efficacy variables included complete haematologic response (CHR) and reduction of the driver mutation JAK2V617F. The safety variable was treatment-related adverse events (TRAEs). RESULTS: A clear relationship between the exposure to ropeginterferon alfa-2b and CHR was observed, with an increase in drug exposure resulting in an increased probability of achieving CHR. Similar CHR probabilities were observed in the third and fourth quantiles of the average concentration at Week 24. The results from the exposure-JAK2V617F model indicated that the JAK2V617F allele burden decreased with increasing exposure to ropeginterferon alfa-2b and baseline body surface area. Exposure-safety analysis revealed a risk of AEs associated with transaminase abnormalities, which were not associated with clinical significance. CONCLUSIONS: Our analyses have shown that patients with PV treated with ropeginterferon alfa-2b had an increased probability of achieving CHR and a molecular response with acceptable safety risks at the 250-350-500 µg titration dosing regimen. This study has provided the relevant data for the application of a biologics licence of ropeginterferon alfa-2b for PV treatment in China.

A gated group sequential design for seamless Phase II/III trial with subpopulation selection.

BACKGROUND: Due to the high cost and high failure rate of Phase III trials where a classical group sequential design (GSD) is usually used, seamless Phase II/III designs are more and more popular to improve trial efficiency. A potential attraction of Phase II/III design is to allow a randomized proof-of-concept stage prior to committing to the full cost of a Phase III trial. Population selection during the trial allows a trial to adapt and focus investment where it is most likely to provide patient benefit. Previous methods have been developed for this problem when there is a single primary endpoint and two possible populations. METHODS: To find the population that potentially benefits with one or two primary endpoints (e.g., progression free survival (PFS), overall survival (OS)), we propose a gated group sequential design for a seamless Phase II/III trial design with adaptive population selection. RESULTS: The investigated design controls the familywise error rate and allows multiple interim analyses to enable early stopping for efficacy or futility. Simulations and an illustrative example suggest that the proposed gated group sequential design has more power and requires less time and resources compared to the group sequential design and adaptive design. CONCLUSIONS: Combining the group sequential design and adaptive design, the gated group sequential design has more power and higher efficiency while controlling for the familywise error rate. It has the potential to save drug development cost and more quickly fulfill unmet medical needs.

A hybrid design for dose-finding oncology clinical trials.

Identifying the maximum tolerated dose (MTD) and recommending a Phase II dose for an investigational treatment is crucial in cancer drug development. A suboptimal dose often leads to a failed late-stage trial, while an overly toxic dose causes harm to patients. There is a very rich literature on trial designs for dose-finding oncology clinical trials. We propose a novel hybrid design that maximizes the merits and minimizes the limitations of the existing designs. Building on two existing dose-finding designs: a model-assisted design (the modified toxicity probability interval) and a dose-toxicity model-based design, a hybrid design of the modified toxicity probability interval design and a dose-toxicity model such as the logistic regression model is proposed, incorporating optimal properties from these existing approaches. The performance of the hybrid design was tested in a real trial example and through simulation scenarios. The hybrid design controlled the overdosing toxicity well and led to a recommended dose closer to the true MTD due to its ability to calibrate for an intermediate dose. The robust performance of the proposed hybrid design is illustrated through the real trial dataset and simulations. The simulation results demonstrated that the proposed hybrid design can achieve excellent and robust operating characteristics compared to other existing designs and can be an effective model for determining the MTD and recommended Phase II dose in oncology dose-finding trials. For practical feasibility, an R-shiny tool was developed and is freely available to guide clinicians in every step of the dose finding process.

Epigenetic Silencing of PTEN and Epi-Transcriptional Silencing of MDM2 Underlied Progression to Secondary Acute Myeloid Leukemia in Myelodysplastic Syndrome Treated with Hypomethylating Agents.

In myelodysplastic syndrome (MDS), resistance to hypomethylating agents (HMA) portends a poor prognosis, underscoring the importance of understanding the molecular mechanisms leading to HMA-resistance. In this study, P39 and Kasumi-1 cells and their azacitidine-resistant and decitabine-resistant sublines were evaluated comparatively with transcriptomic and methylomic analyses. Expression profiling and genome-wide methylation microarray showed downregulation of PTEN associated with DNA hypermethylation in P39 cell lines resistant to azacitidine and decitabine. This pattern of PTEN dysregulation was also confirmed in a cohort of patients failing treatment with HMA. DNA hypomethylation of MDM2 was detected with downregulation of MDM2 in HMA resistant cell lines. Long-read sequencing revealed significant RNA hypomethylation of MDM2 resulting in alternative splicing and production of a truncated MDM2 transcript in azacitidine-resistant P39 cells. The expression of this MDM2 truncated transcript was also significantly increased in HMA-resistant patients compared with HMA-responsive patients. In conclusion, epigenetic and epi-transcriptomic dysregulation of PTEN and MDM2 were associated with resistance to hypomethylating agents.

Mixture survival trees for cancer risk classification.

In oncology studies, it is important to understand and characterize disease heterogeneity among patients so that patients can be classified into different risk groups and one can identify high-risk patients at the right time. This information can then be used to identify a more homogeneous patient population for developing precision medicine. In this paper, we propose a mixture survival tree approach for direct risk classification. We assume that the patients can be classified into a pre-specified number of risk groups, where each group has distinct survival profile. Our proposed tree-based methods are devised to estimate latent group membership using an EM algorithm. The observed data log-likelihood function is used as the splitting criterion in recursive partitioning. The finite sample performance is evaluated by extensive simulation studies and the proposed method is illustrated by a case study in breast cancer.

Inferring latent heterogeneity using many feature variables supervised by survival outcome.

In cancer studies, it is important to understand disease heterogeneity among patients so that precision medicine can particularly target high-risk patients at the right time. Many feature variables such as demographic variables and biomarkers, combined with a patient's survival outcome, can be used to infer such latent heterogeneity. In this work, we propose a mixture model to model each patient's latent survival pattern, where the mixing probabilities for latent groups are modeled through a multinomial distribution. The Bayesian information criterion is used for selecting the number of latent groups. Furthermore, we incorporate variable selection with the adaptive lasso into inference so that only a few feature variables will be selected to characterize the latent heterogeneity. We show that our adaptive lasso estimator has oracle properties when the number of parameters diverges with the sample size. The finite sample performance is evaluated by the simulation study, and the proposed method is illustrated by two datasets.

Switching to Progressively Reduced Nicotine Content Cigarettes in Smokers With Low Socioeconomic Status: A Double-Blind Randomized Clinical Trial.

INTRODUCTION: The Food and Drug Administration issued an advanced notice of proposed rulemaking for setting a product standard for nicotine levels in cigarettes, with an emphasis on minimally or non-addicting very low nicotine content (VLNC). METHODS: A 33 week, two-arm, double-blind randomized trial conducted in Hershey, Pennsylvania, USA and Washington, DC, USA included adult daily cigarette smokers (≥5 cigarettes per day) with less than a college degree, and who had no plans to quit within the next six months. Participants were randomized to either reduced nicotine content (RNC) study cigarettes tapered every three weeks to a final VLNC (0.2 mg/cigarette) for six weeks or to usual nicotine content (UNC) study cigarettes (11.6 mg/cigarette). Outcomes included acceptability of study cigarettes measured by attrition (primary outcome), compliance, reduction in cigarette dependence and tobacco biomarkers, and post-intervention cessation. RESULTS: The RNC (n = 122) versus UNC (n = 123) group had higher attrition (adjusted Hazard Ratio 3.4; 95% confidence interval [CI] 1.99 to 5.81). At the end of the intervention, cotinine levels were 50% lower in the RNC group (mean group difference -137 ng/mL; 95% CI -172, -102). The RNC group smoked fewer CPD (-4.1; 95% CI -6.44, -1.75) and had lower carbon monoxide levels (-4.0 ppm; 95% CI -7.7, -0.4). Forty seven percent (29/62) of the RNC group were biochemically-confirmed compliant with smoking VLNC cigarettes (mean cotinine = 8.9 ng/ml). At three month follow-up, only compliant VLNC smokers quit with an assisted quit attempt (N = 6/22, 27%). CONCLUSIONS: This study supports a VLNC standard in cigarettes. IMPLICATIONS: Differential dropout and noncompliance indicate some smokers had difficulty transitioning to cigarettes with reduced nicotine. These smokers will benefit from supplemental nicotine in medicinal or noncombustible tobacco products if a nicotine reduction standard is established. Other smokers successfully transitioned to very low nicotine content cigarettes exclusively and substantially reduced their exposure to nicotine.

Dynamic RMST curves for survival analysis in clinical trials.

BACKGROUND: The data from immuno-oncology (IO) therapy trials often show delayed effects, cure rate, crossing hazards, or some mixture of these phenomena. Thus, the proportional hazards (PH) assumption is often violated such that the commonly used log-rank test can be very underpowered. In these trials, the conventional hazard ratio for describing the treatment effect may not be a good estimand due to the lack of an easily understandable interpretation. To overcome this challenge, restricted mean survival time (RMST) has been strongly recommended for survival analysis in clinical literature due to its independence of the PH assumption as well as a more clinically meaningful interpretation. The RMST also aligns well with the estimand associated with the analysis from the recommendation in ICH E-9 (R1), and the test/estimation coherency. Currently, the Kaplan Meier (KM) curve is commonly applied to RMST related analyses. Due to some drawbacks of the KM approach such as the limitation in extrapolating to time points beyond the follow-up time, and the large variance at time points with small numbers of events, the RMST may be hindered. METHODS: The dynamic RMST curve using a mixture model is proposed in this paper to fully enhance the RMST method for survival analysis in clinical trials. It is constructed that the RMST difference or ratio is computed over a range of values to the restriction time τ which traces out an evolving treatment effect profile over time. RESULTS: This new dynamic RMST curve overcomes the drawbacks from the KM approach. The good performance of this proposal is illustrated through three real examples. CONCLUSIONS: The RMST provides a clinically meaningful and easily interpretable measure for survival clinical trials. The proposed dynamic RMST approach provides a useful tool for assessing treatment effect over different time frames for survival clinical trials. This dynamic RMST curve also allows ones for checking whether the follow-up time for a study is long enough to demonstrate a treatment difference. The prediction feature of the dynamic RMST analysis may be used for determining an appropriate time point for an interim analysis, and the data monitoring committee (DMC) can use this evaluation tool for study recommendation.

Analysis of time-to-event data using a flexible mixture model under a constraint of proportional hazards.

Cox proportional hazards (PH) model evaluates the effects of interested covariates under PH assumption without specified the baseline hazard. In clinical trial applications, however, the explicitly estimated hazard or cumulative survival function for each treatment group helps to assess and interpret the meaning of treatment difference. In this paper, we propose to use a flexible mixture model under the PH constraint to fit the underline survival functions. Simulations are conducted to evaluate its performance and show that the proposed mixture PH model is very similar to the Cox PH model in terms of estimating the hazard ratio, bias, confidence interval coverage, type-I error and testing power. Application to several real clinical trial examples demonstrates that the results from this approach are almost identical to the results from Cox PH model. The explicitly estimated hazard function for each treatment group provides additional useful information and helps the interpretation of hazard comparisons.

Approximate confidence limit for the reference scaled bioequivalence with a parallel design.

The reference scaled bioequivalence has been proposed with many successful applications for the highly variable products. The statistical properties for the reference scaled bioequivalence have been studied for the commonly used crossover design. However, a crossover design may not be feasible in a real application such as the biosimilar study, instead a parallel design is a more timely and cost-effective choice. In this paper, the approximate upper confidence interval limit for the linearized criteria in the reference scaled bioequivalence from a parallel design is derived. The performance of the approximation is evaluated through the simulation. The simulation results show that this approximation performs well and gives reasonable power and well-controlled type I error.

Characteristics of Adult Cigarette Smokers Who "Relight" and the Effects of Exposure to Tobacco Smoke Constituents.

INTRODUCTION: About half of smokers relight their cigarette, a habit that is a risk factor for chronic bronchitis and possibly lung cancer. Little is known about the characteristics of smokers who relight and their dependence on nicotine. It is unknown whether relighting affects exposure to tobacco smoke constituents. This study examined the characteristics of relighters of usual brand cigarettes and whether relighting affects exposure to selected tobacco smoke constituents. METHODS: We explored relighting status and frequency, using baseline data from 248 adult smokers participating in studies of reduced nicotine cigarettes in relation to demographic and cigarette characteristics, smoking behaviors, nicotine dependence, biomarkers of exposure (exhaled carbon monoxide, blood cotinine), and biomarkers of oxidative stress (ratio of oxidized/reduced glutathione). RESULTS: 69.4% (n = 172) of subjects reported relighting, and they relit an average of five cigarettes out of 20. Both relighters and non-relighters smoked a mean of 20 cigarettes per day (p = .6). Relighting was significantly associated with higher nicotine dependence, use of longer rod cigarettes, older age, lower income, and unemployment. There were no significant associations between relighting and blood cotinine, exhaled carbon monoxide or measures of oxidized/reduced blood glutathione. CONCLUSIONS: The majority of subjects were relighters, who had higher levels of nicotine dependence than non-relighters. Relighters had similar levels of plasma cotinine and exhaled carbon monoxide to non-relighters. IMPLICATIONS: No study has compared the cigarette characteristics and biomarkers of exposure of adult cigarette smokers who relight with those who do not. Relighting behavior was common in our sample and was associated with low income, not currently working, higher nicotine dependence, cigarette rod length, daily cigarette use years, and a lifetime history of depressed mood.

A flexible parametric survival model for fitting time to event data in clinical trials.

Time-to-event data are common in clinical trials to evaluate survival benefit of a new drug, biological product, or device. The commonly used parametric models including exponential, Weibull, Gompertz, log-logistic, log-normal, are simply not flexible enough to capture complex survival curves observed in clinical and medical research studies. On the other hand, the nonparametric Kaplan Meier (KM) method is very flexible and successful on catching the various shapes in the survival curves but lacks ability in predicting the future events such as the time for certain number of events and the number of events at certain time and predicting the risk of events (eg, death) over time beyond the span of the available data from clinical trials. It is obvious that neither the nonparametric KM method nor the current parametric distributions can fulfill the needs in fitting survival curves with the useful characteristics for predicting. In this paper, a full parametric distribution constructed as a mixture of three components of Weibull distribution is explored and recommended to fit the survival data, which is as flexible as KM for the observed data but have the nice features beyond the trial time, such as predicting future events, survival probability, and hazard function.

Circulating microRNAs in plasma as potential biomarkers for the early detection of prostate cancer.

BACKGROUND: MicroRNAs (miRNAs) have been linked to prostate cancer (PC) risk; however, their role as a screening biomarker for PC has yet to be determined. We examined whether circulating miRNAs in plasma could be potential biomarkers for the early detection of PC among men undergoing prostate needle biopsy. METHODS: Men who had a prostate biopsy due to an abnormal screening test were recruited. Linear regression was used to examine the association between miRNAs in plasma and PC status and to model individual miRNA expression on serum PSA and age to calculate the partial correlation coefficient (r). RESULTS: There were 134 men, aged 46-86 years, included, with 66 men with a PC diagnosis (cases), eight men with no PC diagnosis but atypical lesion, and 60 men without a PC diagnosis (controls). The most statistically significant PC circulating miRNAs were miR-381, miR-34a, miR-523, miR-365, miR-122, miR-375, miR-1255b, miR-34b, miR-450b-5p, and miR-639 after adjusting for age (P-values ≤0.05); however, they were no longer statistically significant after P-value adjustment for multiple comparisons. MiR-671-3p was differentially expressed between black and white cases (P-value = 0.03). Moderate positive correlations with serum PSA were observed for miR-381 overall and among controls (r = 0.43-0.60; P-values ≤0.05) and miR-34a among cases (r = 0.46; P-value = 0.02). CONCLUSIONS: There was no miRNA associated with PC diagnosis after adjusting for age and P-values; however, moderate correlations between miRNAs and serum PSA were observed. Further investigation between miRNAs and PC risk is warranted in a larger population at high risk for PC.

Characteristics of pulmonary complications in non-Hodgkin's lymphoma patients treated with rituximab-containing chemotherapy and impact on survival.

Patients with non-Hodgkin's lymphoma (NHL) receiving rituximab-containing chemotherapy are at risk of developing respiratory complications, but comprehensive information on these complications and their impact on survival is lacking. We performed a retrospective cohort analysis on 123 NHL patients who received rituximab-containing chemotherapy between 2009 and 2016 in order to describe the incidence, etiologies and effect on survival of respiratory complications defined by new or worsening respiratory symptoms requiring diagnostic work-up or hospitalization. Thirty patients (24%) developed respiratory complications during a follow-up time of 825 (555-1338) days after chemotherapy. They had a higher prevalence of congestive heart failure and lung or pleural involvement at diagnosis as compared to patients who did not develop complications. Overall, 58 episodes of pulmonary complications were observed after median (interquartile) times from the first and last rituximab doses of 205 (75-580) days and 27 (14-163) days respectively. Infectious etiologies accounted for 75% of the respiratory complications, followed by heart failure exacerbation, lymphomatous involvement, and ARDS. Two Pneumocystis jirovecii pneumonias were observed, and no complication was ascribed to rituximab toxicity. Respiratory complications required ICU admission in 19 cases (33%) and invasive mechanical ventilation in 14 cases (24%). Using a time-dependent Cox regression analysis, we observed that the occurrence of respiratory complications was associated with a 170% increase in death hazard (hazard ratio 2.65, 95% CI 1.60-4.40, p = 0.001). In conclusion, respiratory complications in NHL patients receiving chemotherapy are relatively frequent, severe, and mostly infectious and are associated with increased mortality.

The predictive potential of hyponatremia for glioblastoma patient survival.

Glioblastoma is a devastating malignancy with a dismal survival rate. Currently, there are limited prognostic markers of glioblastoma including IDH1, ATRX, MGMT, PTEN, EGFRvIII, and others. Although these biomarkers for tumor prognosis are available, a surgical biopsy must be performed for these analyses, which has morbidity involved. A non-invasive and readily available biomarker is sought after which provides clinicians prognostic information. Sodium is an electrolyte that is easily and quickly obtained through analysis of a patient's serum. Hyponatremia has been shown to have a predictive and negative prognostic indication in multiple cancer types, but the role of glioblastoma patients' serum sodium at the time of diagnosis in predicting glioblastoma patient survival has not been determined. We assessed whether hyponatremia at the time of glioblastoma diagnosis correlates to patient survival and show that in our cohort of 200 glioblastoma patients, sodium, at any level, did not significantly correlate to glioblastoma survival, unlike what is seen in multiple other cancer types. We further demonstrate that inducing hyponatremia in an orthotopic murine model of glioblastoma has no effects on tumor progression and survival.

Ecological momentary assessment of smoking behaviors in native and converted intermittent smokers.

BACKGROUND AND OBJECTIVES: About 22% of adult smokers in the U.S. are intermittent cigarette smokers (ITS). ITS can be further classified as native ITS who never smoked daily and converted ITS who formerly smoked daily but reduced to intermittent smoking. Ecological momentary assessment (EMA) was conducted to determine the behaviors and experiences that are associated with the decision to smoke. METHODS: The study included 24 native ITS and 36 converted ITS (N = 60) from the Pennsylvania Adult Smoking Study. A baseline questionnaire, daily log, and an EMA smoking log that assessed emotions, activities, and smoking urges was filled out with each cigarette for 1 week to capture 574 smoking sessions. RESULTS: Both groups had very low levels of cigarette dependence. Both groups were more tempted to smoke in positive or negative situations than situations associated with habituation. EMA showed that the most common emotional state during smoking sessions was positive (47%), followed by negative (32%), neutral (16%), and mixed (5%) emotions. Smokers were more likely to smoke during activities of leisure (48%) than during performative duties (29%), social (16%) or interactive occasions (7%). Converted ITS were more likely to smoke alone compared to native ITS (p < .001). DISCUSSION AND CONCLUSIONS: ITS report minimal levels of dependence when captured on traditional scales of nicotine dependence, yet experience loss of autonomy and difficulty quitting. The majority of the ITS reported positive emotions and leisure activities while smoking, and smoked during the evening. SCIENTIFIC SIGNIFICANCE: The current paper identifies environmental and behavioral factors that are associated with smoking among ITS in real time. (Am J Addict 2018;27:131-138).

Pre- and post-magnetic resonance imaging features of suspicious internal mammary lymph nodes in breast cancer patients receiving neo-adjuvant therapy: Are any imaging features predictive of malignancy?

Internal mammary lymph nodes constitute a major lymphatic chain draining the breast and a route of spread for breast cancer metastases. Both physiologic and metastatic internal mammary lymph nodes enhance on breast magnetic resonance imaging, and the clinical significance of their prevalence, size, and morphology when visualized in a patient with breast cancer remains unknown. We studied the characteristics of internal mammary lymph nodes visualized on breast MRI studies before and after neo-adjuvant therapy in twenty-three patients with newly diagnosed breast cancer. A measured decrease in internal mammary lymph node size on post-neo-adjuvant therapy MRI indicated metastatic involvement. Determining suspicious features of internal mammary nodes on initial diagnostic MRI can aid radiologists in reporting probable IMLN metastases and may alter the course of care for patients with breast cancer. This study concludes that metastatic internal mammary lymph nodes should be considered when more than two ipsilateral internal mammary lymph nodes measuring 6 mm or greater are seen on diagnostic MRI in a patient with newly diagnosed breast cancer.

Sample size allocation in multiregional equivalence studies.

With the increasing globalization of drug development, the multiregional clinical trial (MRCT) has gained extensive use. The data from MRCTs could be accepted by regulatory authorities across regions and countries as the primary sources of evidence to support global marketing drug approval simultaneously. The MRCT can speed up patient enrollment and drug approval, and it makes the effective therapies available to patients all over the world simultaneously. However, there are many challenges both operationally and scientifically in conducting a drug development globally. One of many important questions to answer for the design of a multiregional study is how to partition sample size into each individual region. In this paper, two systematic approaches are proposed for the sample size allocation in a multiregional equivalence trial. A numerical evaluation and a biosimilar trial are used to illustrate the characteristics of the proposed approaches.